Just open it and let it run for as long as possible. Survival of the fittest will determine which cars survive. Lower the mutation rate to try more variations of successful cars from the previous generation, and crank it up to get some fresh mutations that are totally wacko.

It's surprising how awesome it is to just watch that thing crank out weird contraptions.

Edit: I can't remember where I found this link. I hope I didn't find it on DoCo or DoCo's IRC... if I did, I'm sorry for (double)posting someone elses find.

It looks fun, but what's the parameter used to determine when a new car is generated?

Every contraption I've seen so far seems to "survive" for a mere couple of seconds - IMHO the stopping parameter should be "hasn't moved for n seconds", whereas it seems to currently be pretty much random.

It looks fun, but what's the parameter used to determine when a new car is generated?

Every contraption I've seen so far seems to "survive" for a mere couple of seconds - IMHO the stopping parameter should be "hasn't moved for n seconds", whereas it seems to currently be pretty much random.

I think this is simply due to the physics engine running very quickly. Looking on my system, it's evaluating at around 500 fps, so the algorithm is looking well ahead of the graphics and simply knows the moment it's time to cull this machine while the animation is catching up.

It looks fun, but what's the parameter used to determine when a new car is generated?

Every contraption I've seen so far seems to "survive" for a mere couple of seconds - IMHO the stopping parameter should be "hasn't moved for n seconds", whereas it seems to currently be pretty much random.

It seems to progressively last longer depending on how the previous generation scored. It seems the number in parentheses is the "goal" score. If the motorcycle reaches that score, it will consider it a success and generate a new one. At first the goal is really small because it's so random that it's probably not very helpful to allow one to go a long distance. That is, in the beginning, quantity is much more important than quality to help narrow down the mutations. I've charted what I think the UI represents in a screenshot:

Darwinism + geneticism + two-wheeled vehicles = ... awesomeness.

The graph at the top appears to be as follows: The red line appears to be the goal (target) score and the black line appears to be the average score for that generation. Depending on how well each generation does, the goal score goes up or down to help improve each iteration. If no motorcycles reach (abot 50% of the) goal score, it will be lower next time so that it can iterate through more mutations faster.

EDIT: The above is all just a guess based on my observations. I could be wrong about any or all of it.

I was playing with this last weekend. I tried three times, for at least 8-10 hours each, and never was able to evolve something that could get past around 213.

It reminds me of watching those people that make their own (stupid) gliders and then throw the self of the end of piers. You hope that each one will get a bit further, or even fly, each time. But they always just flop right down into the sea.

edit:

maybe that would make a nice game: evolve your "cart", get it to race down a bumpy track and then at the end it fall of the track and you see how far it flies. well, not flies, just drops into oblivion.

This reminds me of those old black-and-white movies you see of inventors rolling out their ridiculous-looking planes with about 20 wings that collapse as soon as the engine starts, set to jaunty music.

This reminds me of those old black-and-white movies you see of inventors rolling out their ridiculous-looking planes with about 20 wings that collapse as soon as the engine starts, set to jaunty music.

@Deozaan - I'm pretty sure that your guess about "goal" score is incorrect. That's just not how genetic algorithms work. You can't pre-set an expected fitness level. The best you can do is to take the best specimens from the generation whatever they are.

It appears that in this implementation, brand new specimens are ONLY generated at generation 0. Thereafter, everything comes from either

A combination of attributes from two parent specimens who scored well in the previous generation

Carrying over verbatim a good specimen from the previous generation

Taking the result of one of the previous operations and applying a random value to an attribute, with a likelihood given by the slider bar at the bottom (defaulting to 5%)

I believe that the graph's two curves show (a) the best specimen of the generation in red, and (b) the average specimen in the generation.

That said, I've got no idea what that parenthetic value really does mean. But it regularly shows an absurdly high value -- far higher than any of my cars have ever reached. And in the succeeding generation, it is *not* the case that my cars that all scored lower than this are discarded. They continue to evolve (generally) forward, using the rules I listed.

That said, I've got no idea what that parenthetic value really does mean. But it regularly shows an absurdly high value -- far higher than any of my cars have ever reached. And in the succeeding generation, it is *not* the case that my cars that all scored lower than this are discarded. They continue to evolve (generally) forward, using the rules I listed.

I think you're right about everything, except that I think my "goal" score idea is correct. I just might not be very clear in my description of what a "goal" score is. Let me try to clarify:

Basically, if a motorcycle reaches the "goal" score, it doesn't bother simulating it any further and just moves on to the next mutation. Thus, it has reached its "goal" and is considered the cream of the crop for its particular generation.

Ideally the algorithm should favor those motorcycles which scored the highest, but there's really no way of knowing how exactly a vehicle that reaches the goal affects the next generation compared to the others that don't.

What I do know is that when none of the vehicles get close to the "goal" score, then the number goes down. But if just one makes it or gets about half way, it goes up (doubles?).